The Covid19 pandemic causes several uncertainties for the upcoming winter semester. If possible within the then valid health regulations, we plan to fully return to the usual mode of classroom teaching with mandatory attendance. Nonetheless, an additional “plan B”-scenario for distance teaching will be prepared and enabled if necessary. A final decision will be made centrally from WU’s rectorate in September 2020.
For the classes in Business Analytics II the alternative scenario would be a full distance mode. During the announced time slots (see list of classes) remote sessions will take place via MS Teams. During these time slots the classes will be streamed online. Attendance is compulsory (via MS Teams), since also the In-Class Assignments will be held online within each session. The final exam will be conducted online, details follow duly.

The course builds upon methods and tools introduced in Business Analytics 1. It deepens the skills of the students by applying the tools to problems within the Marketing area. Beginning with basic data handling skills and progressing through statistical  methods, students get to understand the complexity of business decisions and dependencies between different stages of forecasting and planning processes. Students have to apply the tools to integrated real-world cases covering all topics included in the course. In this context, identification of input factors and underlying assumptions as well as correct interpretation of results are of high importance. Topics include:

1.    Introduction to Marketing and Marketing Research
2.    Basic Data Handling
3.    Basic Data Processing
4.    Data visualization
5.    Hypothesis Tests
6.    Analysis of Variance
7.    Regression Models
8.    Exploratory Factor Analysis

After attending this course, students will be able to understand and apply the principles, methods and tools of business analytics to problems in the Marketing area. This includes how to:

•    Handle data files in R
•    Use visualization tools to identify patterns and trends
•    Formulate and test hypothesis, and interpret their results in a business context
•    Apply analysis of variance, regression analysis and exploratory factor analysis, and interpret the results of such analyses to support data driven decision-making in a business context
•    Forecast based on historical data
•    Interpret the results at each stage and use them for the subsequent planning stages
•    Visualize results on a map

  •    Attendance requirement is met if a student is present for at least 80% of the lectures.

The course is taught using a combination of lectures, class discussions, in-class assignments and practical application of the tools and methods to an integrated case study and other examples.

•    Homework exercises, 30 points (6 homeworks)
•    In-class assignments, 30 points 
•    Final exam, 40 points

In order to pass the class, you need to attend at least 80 % of all classes. If you fulfill these criteria, the following grading scale will be applied:
•    Excellent (1): 87.5% - 100.0%
•    Good (2): 75.0% - <87.5%
•    Satisfactory (3): 62.5% - <75.0%
•    Sufficient (4): 50.0% - <62.5%
•    Fail (5): <50.0%